The Correlative Brain: Theory and Experiment in Neural Interaction by Jos J. EggermontThe Correlative Brain: Theory and Experiment in Neural Interaction by Jos J. Eggermont

The Correlative Brain: Theory and Experiment in Neural Interaction

byJos J. Eggermont

Paperback | May 21, 2012

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This monograph is the result of a course given to graduate students and to the faculty of the Dept. of Medical Physics and Biophysics of Nijmegen University, Nijmegen, The Netherlands, in the fall of 1984 and 1985. The course was intended to put together experi­ ment, theory, and analysis methods in order to study neural in­ teraction and coding in the brain. The following pages give a survey of neural interaction and its experimental substrate: cor­ related neural activity. The basic reason for restricting myself to vertebrate brains was to keep the material concise. As the text developed, however, it became more of a review, than a research monograph, in the attempt to balance theoretical and experimen­ tal aspects in brain research. Consequently, the book can be read from various points of view: that of requiring an overview of theories and theoretical principles, or an overview of experimental studies in neural interaction and the methods that can be used, or with the conviction that theory and experiment cannot be separat­ ed. In the latter case the book should be read from beginning to end. A way to read through the theoretical sections and the ex­ perimental sections of the book is presented in the following flow chart; Theory: /Chap. 2 -Chap. 4 -Chap. 5 ___ <_20_chap.>
Title:The Correlative Brain: Theory and Experiment in Neural InteractionFormat:PaperbackDimensions:307 pages, 23.5 × 15.5 × 0.68 inPublished:May 21, 2012Publisher:Springer-Verlag/Sci-Tech/TradeLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:3642510353

ISBN - 13:9783642510359

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Table of Contents

1 Single-Unit Analysis Versus Population Response Analysis.- 2 Outline of this Book.- 1 Information Coding.- 1.1 Information Coding and Transmission by Single Cells and Cell Populations.- Box A. Information Theory.- 1.2 Cooperative Effects and Ensemble Coding.- 2 Spontaneous Activity.- 2.1 Noise or Information Carrier?.- 2.2 Quantification and Representation.- Box B, Distribution Functions.- 2.3 The Auditory System.- 2.4 The Visual System.- 2.5 Other Brain Areas.- 2.6 Synthesis of Spontaneous Activity Phenomenology.- 3 Receptive Fields.- 3.1 Receptotopic and Nonreceptotopic Receptive Fields.- Box C. Conformal Mapping.- 3.2 Center-Surround Structure.- 3.3 Receptive Field Changes in Central Neurons: Feature Detectors?.- 3.4 Temporal Properties of the Receptive Field.- 4 Single-Neuron Models.- 4.1 Diffusion Models.- Box D. Renewal Theory.- Box E. Master Equation.- 4.2 Discrete Input Models.- 4.3 Neural Interaction - Black Box - Models.- Box E Laplace Transforms.- 5 Neural Network Models.- 5.1 Neurons as Logical Switching Elements.- 5.2 Little-Neurons as Network Elements: Introduction of Probability.- 5.3 Statistical Theories of Memory.- Box G. Statistical Mechanics and the Ising Model.- 5.4 Statistical Neuromechanics.- 5.5 Neural Field Theories.- 5.6 Interaction in Neural Nets.- 6 Multiple Separate Recordings from Neural Nets.- 6.1 Recording from Multiple Sites in the Brain.- 6.2 Separating Multiple-Unit Spike Trains.- 6.2.1 Separation on the Basis of Waveform Parameters.- 6.2.2 Spike Separation on the Basis of the Entire Waveform: Template Matching.- 6.2.3 Optimal Filter Procedures.- 6.2.4 Procedures Based on Cluster Analysis in Signal Space.- Box K Principal Component Analysis.- 6.2.5 Detection and Classification Procedures.- 6.2.6 The Performance of Spike Separation Procedures.- Box L Classification Theory.- 6.2.7 Difficulties Encountered with Spike Separation Procedures.- 7 Representation and Detection of Correlated Neural Activity.- 7.1 Representation of Multiple-Site Recorded Continuous Neural Activity.- Box 1 Stationarity of Random Processes.- 7.2 Representation of Multiunit Spike Trains.- 7.3 Cross-Correlation.- 7.4 Joint Peri-Stimulus-Time Scattergrams.- 7.5 A Hierarchy of Multiunit Representations.- 7.6 Correlation Analysis of Larger Numbers of Neural Units.- 7.7 Are Higher-Order Correlation Analyses Necessary?.- 7.8 Correcting Cross-Correlations for Effects of Stimulus Coupling 142.- 8 Correlated Neuronal Activity Observed in the Vertebrate Brain.- 8.1 The Visual System.- 8.1.1 The Retinal Ganglion Cells.- 8.1.2 From Ganglion Cell to Lateral Geniculate Nucleus.- 8.1.3 Inside the Lateral Geniculate Nucleus.- 8.1.4 The Striate Cortex.- 8.1.5 Geniculo-Striate Connections.- 8.2 The Auditory System.- 8.2.1 The Auditory Nerve.- 8.2.2 The Dorsal Cochlear Nucleus.- 8.2.3 The Auditory Midbrain.- 8.2.4 The Medial Geniculate Body.- 8.2.5 The Geniculocortical Projection.- 8.2.6 The Primary Auditory Cortex.- 8.3 The Somatosensory System.- 8.4 Simultaneous Versus Sequential Single-Unit Recording.- 8.5 The Motor System.- 8.5.1 The Motor Cortex.- 8.5.2 Respiratory Areas in the Brainstem.- 8.5.3 Intercostal Motoneurons and Skeletal Motoneurons.- 8.6 Comparison Between the Sensory and Motor Systems.- 8.7 Correlated Neural Activity and the State of the Animal.- 8.8 Correlated Neural Activity and Cognition.- 9 System Identification from Neural Correlation.- 9.1 Identification on the Basis of Continuous Input and Output Signals.- 9.2 Identification on the Basis of Continuous Input and Discrete Output.- 9.3 Identification Based upon Discrete Input and Discrete Output.- 9.3.1 Linear System Analysis.- 9.3.2 Nonlinear Systems Analysis.- 9.4 Identification Based upon Discrete Input and Continuous Output.- 9.5 When Systems Identification Does Not Work.- 10 Plasticity - The Capacity to Change.- 10.1 The Developing Brain.- 10.1.1 Physiological Signs of Plasticity.- 10.1.2 Morphological Substrates of Plasticity.- 10.2 The Adult Brain.- 10.2.1 Physiological Signs of Plasticity.- Local Changes.- Box K, Classical and Operant Conditioning.- Global Changes.- 10.2.2 Morphological Changes in Adult Brains.- 10.3 Mechanisms and Models for Modifiable Synapses.- 10.3.1 General Considerations.- 10.3.2 Formal Models for Modifiable Synapses.- 10.3.3 Stability Considerations for Modifiable Elements.- 10.3.4 Associative Recall and Learning.- 11 Learning - The Cerebellum.- Box L, Anatomy, Physiology and Pharmacology of the Cerebellum.- 11.1 The Cerebellum as a Timing Device.- 11.2 The Cerebellum as a Perceptron.- 11.2.1 Theoretical Considerations.- 11.2.2 Experimental Evidence.- 11.3 The Cerebellum as a Space-Time Metric.- Box M. Vectors and Tensors in Oblique Frames of Reference.- 12 Learning - The Hippocampus.- 12.1 Types of Memory.- 12.2 Brain Structures Involved in Memory.- Box N. The Hippocampus.- 12.3 A Mechanism of Memory Formation in the Hippocampus.- 12.4 Formal Models of Memory Formation.- 12.5 A Model for the Role of the Hippocampus in Memory.- 13 Learning - The Neocortex.- 13.1 The Neocortex: Pinnacle or Way-Station?.- Box Q The Neocortex.- 13.2 Development Aspects of Neocortical Organizations.- 13.3 The Neocortex as a Self-Organizing System.- 13.3.1 General Considerations.- 13.3.2 Theoretical Descriptions.- Box P Neural Assemblies.- 13.3.3 Relation Between Structural Organization and Assembly Formation.- 13.4 Does the Brain Learn by Selection?.- 14 The Correlative Brain.- 14.1 Correlation, the Basic Mechanism of the Brain?.- 14.1.1 Correlation Is Used in the Formation of Topographic Maps.- 14.1.2 Correlation Is Used and Necessary to Detect Events in the Outside World.- 14.1.3 Correlation Is the Basis of Learning, Association, Pattern Recognition, Novelty Detection, and Memory Recall.- 14.1.4 Correlation, Motor Coordination, and Context- Dependent Behavior.- 14.2 Topographic and Functional Brain Maps.- 14.3 Top-Down and Bottom-Up Approaches to Brain Function.- 14.3.1 An "Integrated Circuit" Approach to Brain Function.- References.